About the job

Geospatial Data Scientist Remote (must be UK-based) Up to £80,000 + Bonus The Opportunity Technify Talent have partnered with a growing technology business developing advanced data-driven systems that operate in complex, real-world environments. Their work sits at the intersection of geospatial analytics, machine learning, and multi-source data, tackling challenging problems around data correlation, tracking, and real-time decision-making. They're now looking for a Geospatial focused Data Scientist to play a key role in solving these problems and shaping how spatial data is used across their platform. The Role You'll be working as part of a newly formed data science team, focusing on spatial analytics and multi-sensor data fusion. This role sits at the intersection of applied statistics, machine learning, geospatial data, and mathematical modelling, with a strong emphasis on solving real-world problems, particularly around quantifying and managing uncertainty across multiple data sources. What You'll Be Doing

  • Developing algorithms for spatial data correlation and fusion
  • Analysing and integrating multi-sensor datasets
  • Applying statistical techniques (Bayesian methods, Kalman/particle filtering, and other uncertainty quantification approaches) to improve predictions and manage uncertainty across data sources
  • Building machine learning models for classification, regression, and tracking
  • Performing feature engineering and dimensionality reduction on spatial data
  • Building tools to visualise and validate model outputs
  • Working closely with engineers to deploy models into production systems What We're Looking For
  • Strong background in applied statistics, spatial data science, or a related quantitative field
  • Experience working with Python; geospatial libraries (GeoPandas, GDAL, Rasterio etc.) are a plus but not essential
  • Solid understanding of statistical modelling and uncertainty quantification, e.g. Bayesian methods, Kalman or particle filtering
  • Experience working with complex or large-scale datasets
  • Ability to work in a cross-functional engineering environment
  • Experience deploying models into production systems If you'd like to learn more about the role, team, or technology, feel free to apply or reach out for a confidential chat.

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